Control Parametrization Enhancing Technique for Solving a Special ODE Class with State Dependent Switch

In this paper, the control parametrization enhancing technique (CPET) is applied to obtain numerical solution to a special class of ordinary differential equations where the right-hand side has state dependent discontinuities. Switching locations corresponding to these discontinuities can be calculated exactly and conveniently. Illustrative examples are provided to demonstrate the novel technique.     

Analysis of error propagation in the ABS class for linear systems

Broyden's backward error analysis technique is applied to evaluate the numerical stability of the ABS class of methods for solving linear systems.Part of this work was done during a stage at the University of Bergamo supported by CNR (Programma Professori Visitatori).     

Numerical Solution of A Class of Systems of Volterra Polynomial Equations of the First Kind

In this paper, a class of second-order systems of Volterra nonlinear integral equations is considered. This class is related to a problem of automatic control of a dynamic object with vector inputs and outputs. A numerical solution technique based on the Newton–Kantorovich method is considered. To verify the efficiency of the algorithms developed, a series of test calculations are carried out.     

On dual Bernstein polynomials and stochastic fractional integro-differential equations

In recent years, random functional or stochastic equations have been reported in a large class of problems. In many cases, an exact analytical solution of such equations is not available and, therefore, is of great importance to obtain their numerical approximation. This study presents a numerical technique based on Bernstein operational matrices for a family of stochastic fractional integro-differential equations (SFIDE) by means of the trapezoidal rule. A relevant feature of this method is the conversion of the SFIDE into a linear system of algebraic equations that can be analyzed by numerical methods. An upper error bound, the convergence, and error analysis of the scheme are investigated. Three examples illustrate the accuracy and performance of the technique.     

Numerical solution of the Bagley–Torvik equation by the Bessel collocation method

In this article, a numerical technique is presented for the approximate solution of the Bagley–Torvik equation, which is a class of fractional differential equations. The basic idea of this method is to obtain the approximate solution in a generalized form of the Bessel functions of the first kind. For this purpose, by using the collocation points, the matrix operations and a generalization of the Bessel functions of the first kind, this technique transforms the Bagley–Torvik equation into a system of the linear algebraic equations. Hence, by solving this system, the unknown Bessel coefficients are computed. The reliability and efficiency of the proposed scheme are demonstrated by some numerical examples. Copyright © 2012 John Wiley & Sons, Ltd.     

A method of acceleration for a class of multiplicative programming problems with exponent

Multiplicative programming problems with exponent (MPE) have many practical applications in various fields. In this paper, a method for accelerating global optimization is proposed for a class of multiplicative programming problems with exponent under multiplicative constraints using a suitable deleting technique. This technique offers the possibility of cutting away a large part of the currently investigated region in which the globally optimal solution of the MPE does not exist. The deleting technique can accelerate the convergence of the proposed global optimization algorithm. Two numerical examples are given to illustrate the feasibility of the deleting technique.     

A SELF-ADAPTIVE TECHNIQUE FOR A KIND OF NONLINEAR CONJUGATE GRADIENT METHODS

Conjugate gradient methods are a class of important methods for unconstrained optimization, especially when the dimension is large. In 2001, Dai and Liao have proposed a new conjugate condition, based on it two nonlinear conjugate gradient methods are constructed. With trust region idea, this paper gives a self-adaptive technique for the two methods. The numerical results show that this technique works well for the given nonlinear optimization test problems.     

A new approach for solving a class of nonlinear integro-differential equations

In this paper, a new technique for solving a class of quadratic integral and integro-differential equations is introduced. The main advantage of this technique is that it can replace the nonlinear problem by an equivalent linear one or by another simpler nonlinear one. The convergence of the series solution is proved. Convergence analysis is reliable enough to estimate the maximum absolute truncated error of the series solution. Some numerical examples are introduced to verify the efficiency of the new technique.     

A new semi-analytical collocation method for solving multi-term fractional partial differential equations with time variable coefficients

The aim of this paper is to present a new numerical method for solving a wide class of fractional partial differential equations (FPDEs) such as wave-diffusion equations, modified anomalous fractional sub-diffusion equations, time-fractional telegraph equations. The proposed method is based on the Fourier series expansion along the spatial coordinate which transforms the original equation into a sequence of multi-term fractional ordinary differential equations (ODEs). These fractional equations are solved by the use of a new efficient numerical technique – the backward substitution method. The numerical examples confirm the high accuracy and efficiency of the proposed numerical scheme in solving FPDEs with variable in time coefficients.     

Generalized fast automatic differentiation technique

A new efficient technique intended for the numerical solution of a broad class of optimal control problems for complicated dynamical systems described by ordinary and/or partial differential equations is investigated. In this approach, canonical formulas are derived to precisely calculate the objective function gradient for a chosen finite-dimensional approximation of the objective functional.     

Enlarging the domain of convergence for multiple shooting by the homotopy method

Summary The homotopy method is a frequently used technique in overcoming the local convergence nature of multiple shooting. In this paper sufficient conditions are given that guarantee the homotopy process to be feasible. The results are applicable to a class of two-point boundary value problems. Finally, the numerical solution of two practical problems arising in physiology is described.     

具有分布时滞耦合神经网络模型的全局同步性分析

本文研究了具分布时滞的神经网络的全局同步性.通过应用Lyapunov泛函和线性矩阵不等式,获得了关于模型全局同步性的几个判定准则,并通过对相关例子进行了数值的仿真,模拟结果与理论分析吻合.     

Decentralized robust model reference adaptive control for interconnected time-delay systems

In this paper, the problem of decentralized robust model reference control for a class of interconnected time-delay systems is investigated. The interconnections with time-varying time delays considered are high order and the gains are not known. A class of decentralized adaptive feedback controllers are proposed, which can render the resulting closed-loop error system uniformly ultimately bounded stable. A numerical example is given to show the feasibility and effectiveness of the proposed design techniques.     

An adaptive domain decomposition method for the Hamilton–Jacobi–Bellman equation

In this paper, we propose an efficient algorithm for a Hamilton–Jacobi–Bellman equation governing a class of optimal feedback control and stochastic control problems. This algorithm is based on a non-overlapping domain decomposition method and an adaptive least-squares collocation radial basis function discretization with a novel matrix inversion technique. To demonstrate the efficiency of this method, numerical experiments on test problems with up to three states and two control variables have been performed. The numerical results show that the proposed algorithm is highly parallelizable and its computational cost decreases exponentially as the number of sub-domains increases.     

LMI optimization approach to stabilization of time-delay chaotic systems

Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, this paper proposes a novel control method for stabilization of a class of time-delay chaotic systems. A stabilization criterion is derived in terms of LMIs which can be easily solved by efficient convex optimization algorithms. A numerical example is included to show the advantage of the result derived.     

An <Emphasis Type="Italic">h</Emphasis>-adaptive RKDG method with troubled-cell indicator for one-dimensional detonation wave simulations

In this work, we discuss an extension of the adaptive technique in Zhu and Qiu (J. Comput. Phys. 228, 6957-6976 2009) to design an h-adaptive Runge-Kutta discontinuous Galerkin (RKDG) method for the simulations of several classical one-dimensional detonation waves. The TVB troubled-cell indicator is employed to detect the troubled cells which are believed to contain the discontinuities. An adaptive mesh is generated at each time-level by refining the troubled cells and coarsening the others. A recursive multi-level mesh refinement technique is designed to avoid the problem that the detonation front moves so fast that there are not enough cells to resolve the detonation front before it leaves. We describe the numerical implementation in detail including the adaptive procedure, solution reconstruction method and troubled-cell indicator. Furthermore, a high order positivity-preserving technique is employed for the robustness of our algorithm. Extensive numerical tests are conducted to show the effectiveness of the adaptive strategy and advantages of our adaptive method over the fixed-mesh RKDG method in saving the computational storage and improving the solution quality.     

Numerical solution of multiterm variable‐order fractional differential equations via shifted Legendre polynomials

In this paper, shifted Legendre polynomials will be used for constructing the numerical solution for a class of multiterm variable‐order fractional differential equations. In the proposed method, the shifted Legendre operational matrix of the fractional variable‐order derivatives will be investigated. The fundamental problem is reduced to an algebraic system of equations using the constructed matrix and the collocation technique, which can be solved numerically. The error estimate of the proposed method is investigated. Some numerical examples are presented to prove the applicability, generality, and accuracy of the suggested method.     

Nonlinear feedback controllers and compensators: a state-dependent Riccati equation approach

State-dependent Riccati equation (SDRE) techniques are rapidly emerging as general design and synthesis methods of nonlinear feedback controllers and estimators for a broad class of nonlinear regulator problems. In essence, the SDRE approach involves mimicking standard linear quadratic regulator (LQR) formulation for linear systems. In particular, the technique consists of using direct parameterization to bring the nonlinear system to a linear structure having state-dependent coefficient matrices. Theoretical advances have been made regarding the nonlinear regulator problem and the asymptotic stability properties of the system with full state feedback. However, there have not been any attempts at the theory regarding the asymptotic convergence of the estimator and the compensated system. This paper addresses these two issues as well as discussing numerical methods for approximating the solution to the SDRE. The Taylor series numerical methods works only for a certain class of systems, namely with constant control coefficient matrices, and only in small regions. The interpolation numerical method can be applied globally to a much larger class of systems. Examples will be provided to illustrate the effectiveness and potential of the SDRE technique for the design of nonlinear compensator-based feedback controllers.     

On a method of Atkinson for evaluating domain integrals in the boundary element method

We have shown how to couple a numerical method due to Atkinson for computing particular solutions to a class of elliptic differential equations with a variety of boundary element methods, which alleviates the problem of domain discretization for solving inhomogeneous equations. When the inhomogeneous term is of the form typically used in the dual reciprocity method, Atkinson's formula is such that only boundary integrals need to be approximated numerically. If this method is coupled with the method of potentials, it results in a computational technique which requires neither boundary nor domain discretization. Some numerical results are given validating our approach.     

Finding representations for an unconstrained bi-objective combinatorial optimization problem

Typically, multi-objective optimization problems give rise to a large number of optimal solutions. However, this information can be overwhelming to a decision maker. This article introduces a technique to find a representative subset of optimal solutions, of a given bounded cardinality for an unconstrained bi-objective combinatorial optimization problem in terms of \(\epsilon \)-indicator. This technique extends the Nemhauser–Ullman algorithm for the knapsack problem and allows to find a representative subset in a single run. We present a discussion on the representation quality achieved by this technique, both from a theoretical and numerical perspective, with respect to an optimal representation.